Breast cancer is a common cancer of women and a common cause of cancer deaths. Mammography is an imaging modality which has provided some effectiveness in the early detection of clinically occult breast cancer, and is viewed by some to be a primary imaging modality for breast cancer screening.
However, mammography has been considered by some to have limitations in its ability to detect cancer, with one reported sensitivity being estimated at 80-85%. This limitation may result from the obscuration of the tumor by superimposed fibroglandular tissue. Limitations in sensitivity have stimulated the evaluation of adjunctive imaging modalities for breast cancer screening. MRI (Magnetic Resonance Imaging) is known, and breast MRI is one of these imaging tools.
One benefit of MRI is its delineation of soft tissue and its ability to image the breast in fine sections dynamically and in multiple planes thereby providing four-dimensional information. The basis of MR enhancement of breast cancer relates to vascularity of lesions and vessel permeability. Invasive breast cancer shows increased vascularity with an increased permeability of this neovascularity leading to an early uptake and early washout phenomenon. In addition, invasive breast cancers tend to have increased vascularity at the periphery leading to a rim-enhancing pattern of lesions. The pattern of enhancement of DCIS can be variable including both ductal and regional enhancement.
Advances have been made in the field of breast MRI, however, there is no well-defined standard or optimal imaging technique for performing contrast-enhanced breast MRI. In addition, there are no standardized interpretation criteria and no unified definition of what constitutes clinically important contrast enhancement. There have been several approaches to image interpretation: 1) evaluation of enhancement kinetics or patterns of contrast enhancement 2) evaluation of lesion morphology or appearance. Some researchers believe that malignant lesions consistently enhance and do so earlier and to a greater degree than benign lesions. Some researchers have utilized a quantitative approach to kinetic evaluation or enhancement patterns. Others have used a qualitative method for evaluation of the overall shape of the enhancement curve when attempting to distinguish benign from malignant lesions.
Referring to FIG. 1, there are shown three types of contrast enhancement patterns in terms of time/enhancement intensity curves. Type I shows a steady enhancement where a persistent increase in signal intensity is present after 2 minutes. Type II shows a plateau, where the maximum signal intensity is achieved in 2 minutes and remains constant. Type III shows a washout, where the maximum achieved signal is demonstrated by 2 minutes and decreases with time. Benign lesions are believed to demonstrate Type I curve and malignant lesions are believed to demonstrate Type III.
In breast MRI scans, a contrast agent injected into the bloodstream can provide information about blood supply to the breast tissues. Usually, several scans are taken, with one before the contrast agent is injected and at least one after the contrast agent is injected. The pre-contrast and post-contrast images are compared and areas of difference before and after injection are highlighted. It should be recognized that if the patient moves even slightly between the two scans, detail information in the images may be distorted, thus resulting a loss of information due to a misregistration of the two scans acquired at the different times. Image registration may be required to reduce artifacts due to patient movement.
A study of these contrast enhancement patterns enables the identification of three different tissue types due to their differential contrast uptake and washout properties as illustrated in FIG. 1. Typically, cancerous tissue shows a high and fast uptake due to a proliferation of “leaky” angiogenic microvessels, while normal and fatty tissues show little uptake. The uptake (dynamic) curves can be fitted using a pharmacokinetic model to give a physiologically relevant parameterisation of the curve (refer to P. S. Tofts, B. Berkowitz, M. Schnall, “Quantitative analysis of dynamic Gd-DTPA enhancement in breast tumours using a permeability model”, Magn Reson Med 33, pp 564-568, 1995). U.S. Pat. No. 6,353,803 (Degani), U.S. Patent Application No U.S. 2006/0018548 (Chen) and U.S. Patent Application No U.S. 2005/0074149 (Niemeyer) applied techniques and pre-selected thresholds to differentiate Type I, II and III curves. U.S. Pat. No. 6,112,112 (Gilhuijs) performed variance processing on the temporally obtained image data to derive variance image data defining a variance image indicative of variation of voxels. Variance images were used to perform breast volume segmentation, breast border removal, lesion enhancement, determination of the bounding sphere, computation of a 3D search volume, suppression of surrounding structures, and volume growing, then determine an estimate of the extent of the tumor (lesion) in the breast. The limitation of the above approaches is that the interpretation based on temporal analysis of contrast enhancement only.
A study of these curves of time/enhancement parameters has been used clinically to identify and characterize tumors into malignant or benign classes, although the success has been variable with generally good sensitivity but often very poor specificity (for example, refer to S. C. Rankin “MRI of the breast”, Br. J. Radiol 73, pp 806-818, 2000).
Lesion morphology such as architectural features identified on high spatial resolution images has been used to characterize lesions as to benign or malignant. Features that have been reported as suggestive of malignancy include a mass with irregular or spiculated borders and peripheral or ductal enhancement. Features of benignity include a mass with smooth or lobulated borders, no enhancement, nonenhancing internal septa and patchy parenchymal enhancement. In mammography, lesion margins represent the interface between the lesion and the adjacent parenchyma. The margin interface on MRI represents the interface between the area of vascularity and the surrounding tissue. It should be noted that the mammographic features will not necessarily be the same on a mammography and MRI image.
Applicants have noted that an integrated interpretation strategy where enhancement kinetics and morphologic features are used together would potentially obtain superior outcomes compared to the use of either method alone.
Accordingly, there exists a need for an approach to effectively combine temporal and spatial analysis of the 4D MRI images to automatically detect and diagnose breast lesions in dynamic MRI images. While U.S. Pat. No. 6,317,617 (Gilhuijs) extracts features from an identified lesion to characterize and diagnosis the lesion, the approach provides an analysis of a pre-identified suspicious area.
The present invention provides an automated detection and characterization of breast lesions in MRI images. The method identifies suspicious cancerous areas based on the analysis of time/enhancement properties of the tissues, and characterizes the suspicious areas using spatial and/or temporal features to determine the likelihood of malignancy.